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Michael Bernstein
Human-Centered Artificial Intelligence (AI)
Social Computing
Interactive Technology Design
Societal Impact Of AI
About
Michael Bernstein is a Professor of Computer Science at Stanford University, where he is a Bass University Fellow and Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence. A nationally bestselling author, Michael focuses on designing social, societal, and interactive technologies. This research has been reported in venues such as The New York Times, TED AI, and MIT Technology Review, and Michael himself has been recognized with an Alfred P. Sloan Fellowship and the Computer History Museum's Tech for Humanity Prize. Michael holds a bachelor's degree in Symbolic Systems from Stanford University, as well as a master's degree and a Ph.D. in Computer Science from MIT.
Research Performance Summary
1993-2026
Active Research Span
First Recorded Paper
OPPORTUNITIES FOR PROGRESS
Year:
1993
Citations:
0
Venue:
IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 12 (2)
Latest Recorded Paper
People Can Accurately Predict Behavior of Complex Algorithms That Are Available, Compact, and Aligned
Year:
2026
Citations:
0
Venue:
arXiv preprint arXiv:2601.18966
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Bernstein
Krishna
Research Impact by Period
Papers
21
Citations
217
Avg. Citations / Paper
10.3
H-Index
8
Papers
68
Citations
17366
Avg. Citations / Paper
255.4
H-Index
30
Papers
84
Citations
72883
Avg. Citations / Paper
867.7
H-Index
47
Papers
65
Citations
9018
Avg. Citations / Paper
138.7
H-Index
33
Papers
26
Citations
1119
Avg. Citations / Paper
43
H-Index
11
Papers
2
Citations
0
Avg. Citations / Paper
0
H-Index
0
Papers
3
Citations
201
Avg. Citations / Paper
67
H-Index
2
Papers
1
Citations
0
Avg. Citations / Paper
0
H-Index
0
Contact and Professional Links
Detected Research Keywords
Scale Visual Recognition
Visual Recognition Challenge
Imagenet Scale Visual
Opportunities Risks Foundation
Risks Foundation Models
Visual Genome Connecting
Genome Connecting Language
Connecting Language Vision
Language Vision Crowdsourced
Vision Crowdsourced Dense